Unemployment as a social norm in Germany

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Unemployment as a social norm in GermanyAndrew E. Clark, Andreas Knabe, Steffen Rätzel

To cite this version:Andrew E. Clark, Andreas Knabe, Steffen Rätzel. Unemployment as a social norm in Germany. 2008.�halshs-00586249�

WORKING PAPER N° 2008 - 45

Unemployment as a social norm in Germany

Andrew Clark

Andreas Knabe

Steffen Rätzel

JEL Codes: I31, Z13, J64 Keywords: social norms, unemployment, life satisfaction

PARIS-JOURDAN SCIENCES ECONOMIQUES

LABORATOIRE D’ECONOMIE APPLIQUÉE - INRA

48, BD JOURDAN – E.N.S. – 75014 PARIS TÉL. : 33(0) 1 43 13 63 00 – FAX : 33 (0) 1 43 13 63 10

www.pse.ens.fr

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE – ÉCOLE DES HAUTES ÉTUDES EN SCIENCES SOCIALES ÉCOLE NATIONALE DES PONTS ET CHAUSSÉES – ÉCOLE NORMALE SUPÉRIEURE

Unemployment as a Social Norm in Germany

Andrew Clark*

Paris School of Economics and IZA

Andreas Knabe**

Otto-von-Guericke-University Magdeburg and CESifo

Steffen Rätzel*** Otto-von-Guericke-University Magdeburg

September 1st 2008

Abstract This paper investigates the relationship between the subjective well-being of both the employed and unemployed and regional unemployment rates. While employed men suffer from regional unemployment, unemployed men are significantly less negatively affected. This is consistent with a social-norm effect of unemployment in Germany. We find no evidence of such an offsetting effect for women.

Keywords: social norms, unemployment, life satisfaction JEL codes: I31, Z13, J64

* Corresponding author: PSE, 48 Boulevard Jourdan, 75014 Paris, France. Tel.: +33—43-13-63-29. E-mail:

[email protected]. ** Otto-von-Guericke-University Magdeburg, Faculty of Economics and Management, P.O. Box 4120, 39016

Magdeburg, Germany. Tel.: +49-0391-6718518. E-mail: [email protected]. *** Otto-von-Guericke-University Magdeburg, Faculty of Economics and Management, P.O. Box 4120, 39016

Magdeburg, Germany. Tel.: +49-0391-67-11885. E-mail: [email protected]. We thank the participants at the 8th International SOEP User Conference in Berlin for their helpful

comments.

Unemployment as a Social Norm in Germany 1. Introduction

Unemployment is amongst the most harmful of all experiences for individual well-being.

During the Great Depression, Eisenberg and Lazarsfeld (1938), using descriptive methods,

emphasised that job loss deprived individuals not only of their labor income, but also of the

non-pecuniary benefits of work. The more recent economic literature on subjective well-being

has also addressed this issue. Clark and Oswald (1994), using the first wave of the British

Household Panel Survey (BHPS), showed that unemployment is associated with significantly

lower mental well-being (GHQ) scores. Additional supportive evidence has come from other

countries, for example Germany in Gerlach and Stephan (1996) and Winkelmann and

Winkelmann (1995, 1998), and the United States in Blanchflower and Oswald (2004).

Besides having adverse effects on the mental well-being of those who actually lose their

jobs, unemployment also affects the well-being of individuals in the community of the

unemployed, such as their families, colleagues, and neighbors. In particular, higher

unemployment may reduce the well-being of those who remain in work via a more

pessimistic perception of their own future unemployment prospects. Cobb and Kasl (1977),

Fryer and McKenna (1988), and De Witte (1999) have all emphasized that the anticipation of

redundancy is at least as distressing for individuals as the experience of unemployment itself.

Hartley et al. (1991), in their survey of a number of pieces of work on job insecurity, found

that those with falling perceived job security also report severe uncertainty in other life areas,

impaired mental health (as expressed by psychosomatic symptoms and depression), lower job

satisfaction, reduced organizational commitment and trust in management, resistance to

change and deteriorating industrial relations.

While there would appear to be a fair amount of evidence of the detrimental effect of

surrounding unemployment on the employed, this is less true for the effect of local

unemployment on the unemployed themselves. It has been suggested in the literature that

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Unemployment as a Social Norm in Germany unemployment may hurt the unemployed less the more they see of it around them, as the

stigma from their own unemployment is then reduced. For example, Kessler et al. (1988) find

that it is easier for the unemployed to establish social contacts when others in the local area

are also unemployed. Cohn (1978) finds that unemployed persons’ satisfaction with self is

lower when there is no external cause to which one’s own unemployment can be attributed,

but that generally high unemployment in the region can represent such an external cause.

Economists have recently started to make use of large-scale datasets to quantitatively

examine the effect of unemployment on others. Clark (2003) uses the BHPS to examine the

impact of other’s unemployment both on the employed and on the unemployed. While

regional unemployment generally has a negative effect on the employed, there is evidence of

an opposite effect for unemployed men: the well-being of unemployed men rises with the

regional unemployment rate. Even at the household and partner level, men report higher well-

being scores if they are not the only unemployed person in the household. These results are

consistent with a “social norm” effect of unemployment. Similar results have been found for

the United Kingdom (Shields and Wheatley Price, 2005), Australia (Shields et al., 2008),

South Africa (Powdthavee, 2007), and Switzerland (Stutzer and Lalive, 2004).

In this paper, we follow the methodology of Clark (2003) and, using data for Germany,

examine how the subjective well-being of the employed and the unemployed is affected by

regional unemployment rates. We find strong evidence for a social norm effect of

unemployment in Germany. While employed men suffer from unemployment in their region,

unemployed men are significantly less negatively affected. For women, however, no such

offsetting effect appears to exist.

This paper is structured as follows. In the next section, we describe the data and the

estimation methodology. Section 3 contains the empirical results, and the last section provides

a summary and concludes.

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Unemployment as a Social Norm in Germany 2. Data and Methodology

We use data from 23 waves (1984-2006) of the German Socio-Economic Panel (GSOEP),

a representative longitudinal study of private households in Germany.1 We include all

individuals aged between 21 and 60 who are either employed or registered unemployed. This

yields roughly 60,000 observations (from 9,000 different individuals) for each sex. As a proxy

utility measure, we use self-rated life satisfaction, measured on a scale from 0 to 10 (where 0

denotes “not satisfied at all” and 10 stands for “completely satisfied”).

We explain life satisfaction by a fairly standard set of variables, such as income, family

status, education etc. To examine the personal and external effects of unemployment, we also

include the respondent’s own employment status and the regional unemployment rate. To test

for a social norm effect, we include an interaction term between own employment status and

the regional unemployment rate. Our multivariate analysis is based on the same regression

specification as Clark (2003, p. 332):

( ) ittitititititiit XUERATEUEUERATEUELS εµγβββα ++++++= '*321 (1)

where αi is an individual fixed effect, UEit is a dummy taking the value 1 if the individual is

officially registered as unemployed at the German Employment Office, and UERATEit is a

measure of the regional unemployment rate (at the German federal state level).2 The vector Xit

is a set of standard control variables that might potentially be correlated with individual well-

being (such as income and marital status), µt are wave dummies, and εit is a random error

term.

Building on the social norm literature cited in the Introduction, we formulate three prior

hypotheses regarding equation (1): 01 <β (the unemployed are less happy than the

1 The data used in this publication were made available by the German Socio-Economic Panel Study (GSOEP) at the German Institute for Economic Research (DIW), Berlin. The data were extracted using the Add-On-package PanelWhiz for Stata: see Haisken-DeNew and Hahn (2006) for details. 2 These unemployment rates were obtained from the German Employment Office (2008).

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Unemployment as a Social Norm in Germany employed); 02 <β (higher regional unemployment makes the employed less happy); and

03 >β (there is a counteracting social norm effect for the unemployed, who are thus less

negatively affected by regional unemployment than are the employed).

3. Results

3.1. Descriptive Statistics

A simple and illustrative way of demonstrating a social norm effect of unemployment is to

compare the life satisfaction gap between the employed and the unemployed in regions with

different unemployment rates and check whether this life satisfaction gap is smaller in higher

unemployment regions. Figures 1 and 2 illustrate, for men and women respectively, the

relationship between regional unemployment and the life satisfaction gap between the

employed and the unemployed. Each point in these figures represents a German federal state,

averaged over five-year periods from 1984 to 2006.

Figure 1 reveals a negative relationship between regional unemployment and the employed-

unemployed well-being gap for men. This is consistent with a social norm effect: there is

always a life satisfaction gap between the employed and the unemployed, but joblessness

hurts less in regions where there is more unemployment. Figure 2 presents the same data for

women. It is difficult to detect any social norm effect here, with the relationship appearing to

be positive, if anything, rather than negative.

- Figures 1 and 2 about here -

3.2. Regression results

To analyze the effects of aggregate unemployment on individual well-being, we now turn

to econometric analysis. Since life satisfaction is an ordinal variable that is potentially

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Unemployment as a Social Norm in Germany affected by individual-specific unobservable characteristics, we apply a fixed-effect

conditional logit model (see Ferrer-i-Carbonell and Frijters, 2004).

The results are presented in the first two columns of Table 1. The estimation results with

German data are consistent with those found in a number of other countries (see the

references in our Introduction). As expected, own unemployment is associated with sharply

lower well-being. With respect to the effects of others’ unemployment, the coefficient on the

main effect of regional unemployment is significant and negative. This highlights two

channels via which unemployment reduces individual welfare. It first generates well-being

losses for those who become unemployed, but also produces negative externalities on those

who remain employed.

When we look at the effect of regional unemployment on unemployed men, we see that

there is a strong opposing effect (statistically significant at the 10% level). Unemployed men

suffer significantly less from surrounding unemployment than they would if they were

employed. The estimated positive coefficient on the interaction term is, however, smaller in

absolute size than the negative coefficient on the unemployment rate. Both the unemployed

and employed are negatively affected by regional unemployment, but the magnitude of this

effect is much smaller for the former.

There is no evidence of a social norm effect for women. The main effect of regional

unemployment is negative (although statistically insignificant), and, contrary to men,

unemployed women feel worse in regions with higher unemployment rates.

The other determinants of life satisfaction, which we include as control variables in our

regression, have the expected signs for both sexes. Income is strongly positively correlated

with well-being. Working part-time is less good than full-time employment. Cohabiting or

being married is associated with higher life satisfaction than being single, while being

divorced and living without a new partner reduces men’s life satisfaction, but not that of

women. Widowhood has an insignificant effect for both sexes. Respondents with children

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Unemployment as a Social Norm in Germany report (insignificantly) higher life satisfaction scores. Last, education is positive, although

significantly so only for women, and people are significantly less happy in their forties than in

their twenties.

- Table 1 about here -

While widely-used in the “economics of happiness” literature, the conditional fixed effect

logit model suffers from two disadvantages. First, the recoding of eleven life satisfaction

scores into just two categories obviously discards a lot of information. Second, and perhaps

more importantly, it is not necessarily true that the signs of the estimated coefficients

correspond to the signs of their marginal effects. Ai and Norton (2003) show that non-linear

regression models suffer from this problem and that special care has to be taken when

interpreting the coefficients. To deal with both issues, we appeal to a novel estimation method

that retains the original dependent variable and avoids the pitfalls of non-linear models – the

Probit-adjusted ordinary least squares (POLS) approach of Van Praag and Ferrer-i-Carbonell

(2004). In contrast to standard OLS, which assumes equal distances between the life

satisfaction categories, POLS transforms these latter on the entire real axis by using the

overall sample distribution. Van Praag (2005) shows that the results generated by traditional

ordered probit and Probit OLS are the same up to a multiplication factor. The advantage of

POLS, as compared to ordered probit, lies in the possibility of applying panel data methods,

such as individual fixed effects.

Columns 3 and 4 of Table 1 present the results from a POLS regression with fixed effects.

The results are qualitatively similar to those from the conditional logit estimation. Own

unemployment hurts, as previously, and the main effect of regional unemployment is

negative, for both men and women. The social norm effect, however, is again only found for

men. In this specification, the sum of the main and interaction effects of regional

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Unemployment as a Social Norm in Germany unemployment is positive (although statistically insignificant), suggesting that others’

unemployment may even increase the well-being of unemployed men. Women, on the other

hand, are adversely affected by regional unemployment whether they be employed or

unemployed. Both POLS and conditional logit estimation thus suggest that regional

unemployment produces negative externalities on the employed, but there is evidence of a

social norm effect, whereby greater regional unemployment reduces well-being less, or may

at the limit even be welcome, for unemployed men.

4. Conclusion

Unemployment is widely considered as generating negative externalities. Greater

unemployment makes the employed feel less secure about being able to keep their job in the

future, while the unemployed suffer from worse prospects of finding a new job. However, in

addition to these negative effects, there may well be a counteracting positive impact for the

unemployed: if more people suffer the same fate, one’s own unemployment might be easier to

bear. This is termed the “social norm effect of unemployment”. In this paper, we see whether

a social norm effect of unemployment – whereby aggregate unemployment reduces the well-

being of the employed, but has a smaller negative, or even positive, effect on the unemployed

– can be found in Germany. Our panel regression analysis suggests that, while both employed

men and women feel worse in regions with higher unemployment, there is evidence of a

social norm effect for unemployed men (but not unemployed women). This same disparity

between men and women was found in BHPS data in Clark (2003).

References

Ai, C. / Norton, E. (2003), Interaction terms in logit and probit models, Economics Letters 80,

123-129.

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Unemployment as a Social Norm in Germany Blanchflower, D. / Oswald, A. (2004), Well-being over time in Britain and the USA, Journal

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Clark, A.E. (2003), Unemployment as a Social Norm: Psychological Evidence from Panel

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Cobb, S. / Kasl, S. (1977), Termination: The Consequences of Job Loss, Cincinnati.

Cohn, R. (1978), The effect of employment status change on self-attitudes, Social Psychology

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De Witte, H. (1999), Job Insecurity and Psychological Well-being: Review of the Literature

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Eisenberg, P. / Lazarsfeld, P. (1938), The psychological effects of unemployment,

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Ferrer-i-Carbonell, A. / Frijters, P. (2004), How important is methodology for the estimates of

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Fryer, D. / McKenna, S. (1988), Redundant skills: temporary unemployment and mental

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German Employment Office (2008), Statistik der BA- Detaillierte Informationen – Zeitreihen,

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Haisken-DeNew, J. P. / Hahn, M. (2006), PanelWhiz: A Flexible Modularized Stata Interface

for Accessing Large Scale Panel Data Sets, http://www.panelwhiz.eu.

Hartley, J. / Jacobson, D. / Klandermans, B. / van Vuuren, T., with Greenhalgh, L. / Sutton, R.

(1991), Job Insecurity: Coping with jobs at risk, London.

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Unemployment as a Social Norm in Germany Kessler, R. / Turner, J. / House, J. (1988), The effects of unemployment on health in a

community survey: main, modifying, and mediating effects, Journal of Social Issues 44,

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Powdthavee, N. (2007), Are there geographical variations in the psychological cost of

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Shields, M. / Wheatley Price, S. / Wooden, M. (2008), Life Satisfaction and the Economic and

Social Characteristics of Neighbourhoods, forthcoming in Journal of Population Economics.

Stutzer, A. / Lalive, R. (2004), The role of social work norms in job searching and subjective

well-being, Journal of the European Economic Association 2, 696-719.

Van Praag, B. M. S. (2005), The Connection between Old and New Approaches to Financial

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Unemployment as a Social Norm in Germany Figure 1: The Employed-unemployed life satisfaction gap and regional unemployment: Men

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Notes to both figures. Observations by German Federal States averaged over the following periods: 1984-1988 (only former West Germany), 1989-1993 (1991-1993 for East Germany), 1994-1998, 1999-2003, and 2004-2006. We exclude the three city states (Berlin, Hamburg, Bremen) due to a lack of sufficient observations (less than three observations per period). Key: B = Bavaria, BB = Brandenburg, BW = Baden-Württemberg, H = Hessen, LS = Lower Saxony, MV = Mecklenburg-West Pommerania, NW = North Rhine-Westphalia, RS = Rhineland-Palatinate/Saarland, S = Saxony, SA = Saxony-Anhalt, SH = Schleswig-Holstein, and T = Thuringia.

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Unemployment as a Social Norm in Germany

Table 1: Regression results

Conditional FE logit Probit-adjusted OLS

(1) (2) (3) (4)

Men Women Men Women

Reference category

Full-time employed, single, less

than 30 years old

Full-time employed, single, less

than 30 years old

Full-time employed, single, less

than 30 years old

Full-time employed, single, less

than 30 years old

Unemployed -1.170*** -0.344*** -0.625*** -0.235*** (0.117) (0.116) (0.035) (0.037)

UE Rate -0.026*** -0.012 -0.010*** -0.006** (0.008) (0.008) (0.002) (0.003)

UE Rate x unemployed 0.015* -0.031*** 0.014*** -0.005** (0.008) (0.008) (0.002) (0.003)

Household income 0.344*** 0.315*** 0.120*** 0.106*** (per capita) /1000 (0.033) (0.035) (0.009) (0.010)

Part-time -0.282*** -0.158*** -0.102*** -0.078*** (0.071) (0.035) (0.022) (0.011)

Cohabitation 0.333*** 0.456*** 0.125*** 0.156*** (0.049) (0.058) (0.015) (0.018)

Married 0.524*** 0.344*** 0.187*** 0.122*** (0.060) (0.068) (0.019) (0.022)

Divorced -0.522*** -0.065 -0.200*** -0.051* (0.085) (0.084) (0.026) (0.027)

Widowed -0.036 -0.189 -0.017 -0.166*** (0.210) (0.140) (0.065) (0.045)

Number of children 0.015 0.024 0.007 0.007 (0.018) (0.022) (0.006) (0.007)

Years of education 0.003 0.044** -0.002 0.012** (0.017) (0.020) (0.005) (0.006)

30 ≤ age < 40 -0.021 -0.013 -0.012 -0.005 (0.043) (0.048) (0.013) (0.016)

40 ≤ age < 50 -0.132** -0.073 -0.046** -0.040* (0.066) (0.073) (0.020) (0.023)

50 ≤ age -0.103 -0.112 -0.047* -0.044 (0.091) (0.101) (0.028) (0.032)

Individual fixed effects yes yes yes yes Wave dumies yes yes yes yes Log likelihood -30161.263 -25143.647 R² 0.057 0.041 Number of observations 64774 54338 69712 59466

Notes. Standard errors in parentheses. * denotes significance at the 10% level, ** at the 5% level, and *** at the 1% level.

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